Genome-wide association studies (GWAS) have discovered numerous genetic variants associated with human behavioural traits. However, behavioural traits are subject to misreports and longitudinal changes (MLC) which can cause biases in GWAS and follow-up analyses. Here, we demonstrate that individuals with higher disease burden in the UK Biobank (n = 455,607) are more likely to misreport or reduce their alcohol consumption levels, and propose a correction procedure to mitigate the MLC-induced biases. The alcohol consumption GWAS signals removed by the MLC corrections are enriched in metabolic/cardiovascular traits. Almost all the previously reported negative estimates of genetic correlations between alcohol consumption and common diseases become positive/non-significant after the MLC corrections. We also observe MLC biases for smoking and physical activities in the UK Biobank. Our findings provide a plausible explanation of the controversy about the effects of alcohol consumption on health outcomes and a caution for future analyses of self-reported behavioural traits in biobank data.

全基因组关联研究 (GWAS) 发现了许多与人类行为特征相关的遗传变异。然而，行为特征容易受到误报和纵向变化 (MLC) 的影响，这可能会导致 GWAS 和后续分析出现偏差。在这里，我们证明了英国生物库中疾病负担较高的个体（n= 455,607) 更有可能误报或减少他们的酒精消费水平，并提出纠正程序以减轻 MLC 引起的偏差。通过 MLC 校正去除的饮酒 GWAS 信号在代谢/心血管特征方面得到了丰富。在 MLC 校正后，几乎所有先前报告的饮酒与常见疾病之间遗传相关性的负面估计都变为正面/不显着。我们还在英国生物库中观察到 MLC 对吸烟和体育活动的偏见。我们的研究结果为关于饮酒对健康结果的影响的争议提供了一个合理的解释，并为未来分析生物样本库数据中的自我报告行为特征提供了警告。